A cognitive health management system for the elderly based on virtual reality technology

Abstract

This invention relates to the field of cognitive health management technology, specifically a cognitive health management system for the elderly based on virtual reality technology. The system includes an initial login module, a scene acquisition module, a data acquisition module, a cognitive health assessment module, a decision generation module, and a cognitive health management module. The initial login module acquires various selection data from the user. The data acquisition module collects various physical and audio-visual data from the user in real time. The decision generation module generates cognitive health training decisions based on the causes of abnormalities and a preset information database. The cognitive health management module processes the scene training decisions and user feedback to obtain rehabilitation training scenarios and plans that meet the user's needs. This invention addresses the problem of infrequent communication between the elderly and doctors, making it difficult to accurately determine the elderly's cognitive health level based solely on examination data, leading to diagnostic errors.

Description

Technical Field

[0001] This invention relates to the field of cognitive health management technology, and more specifically to a cognitive health management system for the elderly based on virtual reality technology. Background Technology

[0002] Cognitive health in older adults primarily refers to their brain cognitive health. Brain cognitive health means that the brain possesses age-appropriate cognitive functions and mental and psychological states, without any brain diseases affecting normal brain function. Brain cognitive health management encompasses the comprehensive monitoring and assessment of an individual's or group's brain cognitive health, providing health consultation and guidance, and intervening in individuals with cognitive impairments and high-risk groups. It is a crucial means of preventing and slowing the progression of cognitive impairment and an important component of health management.

[0003] Brain cognitive health management encompasses the screening, assessment, and intervention of brain cognitive health status. Brain cognitive health screening refers to the preliminary examination of the cognitive function and other conditions of potential patients using cognitive function screening tools, auxiliary tests, and imaging examinations. Brain cognitive health assessment refers to the comprehensive evaluation of brain cognitive health status and risk factors based on the preliminary screening results, and the stratification of the population to provide a basis for guiding the implementation of intervention strategies. Brain cognitive health intervention refers to improving brain cognitive health levels through intervention measures such as lifestyle interventions, risk factor management, and cognitive digital therapy, as well as management through regular follow-up and dynamic assessment.

[0004] Currently, existing cognitive health management for the elderly generally requires the elderly and their families to go to the hospital for examinations first, and then communicate with the doctor to determine the specific situation while waiting for the test results. The examination process is quite cumbersome and time-consuming. Furthermore, the number of times the elderly communicate with the doctor is limited, and the cognitive health level of the elderly cannot be accurately determined based solely on the test data, which can lead to errors in the diagnosis.

[0005] Therefore, the present invention provides a cognitive health management system for the elderly based on virtual reality technology to solve the above problems. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, the present invention provides a cognitive health management system for the elderly based on virtual reality technology. This system addresses the problem that the elderly have fewer interactions with doctors, and the cognitive health level of the elderly cannot be accurately determined based solely on examination data, which can lead to errors in the diagnostic results.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A cognitive health management system for the elderly based on virtual reality technology, the system includes:

[0009] The system comprises four modules: an initial login module, which acquires user selection data upon first login; a scenario acquisition module, which retrieves interactive scenarios for cognitive health assessment based on the selected data; a data acquisition module, which collects real-time physical data and audio / video data of the user during interactions within these scenarios; a cognitive health assessment module, which analyzes the physical and audio / video data to obtain the user's cognitive health assessment results; a decision generation module, which analyzes abnormal data in the cognitive health assessment results when the cognitive health level is lower than a preset level, identifies the cause of the abnormality, matches the cause of the abnormality with a preset information database, and generates cognitive health training decisions based on these initial decisions; and a cognitive health management module, which acquires scenario training decisions from the cognitive health training decisions, matches corresponding rehabilitation training scenarios and plans based on these scenarios and user feedback, and periodically evaluates the rehabilitation training results using the cognitive health assessment module to adjust the rehabilitation training plan accordingly.

[0010] Preferably, the scene acquisition module includes: sequentially filtering multiple scenes that match the selected data from the scene database according to the selection order of each selected data; randomly selecting a preset number of scenes from each preset type of scene using a simple random sampling method according to the preset type of scene; the preset number of scenes form various interactive scenes for cognitive health assessment in the cognitive health assessment module.

[0011] Preferably, the cognitive health assessment module includes: using an audio-visual analysis model to perform voice and image analysis on audio-visual data to obtain user performance data; storing various physical data and corresponding performance data into a recording dataset of the corresponding interaction scenario in chronological order; performing fusion evaluation analysis on the corresponding recording dataset based on a preset scenario analysis model for each interaction scenario to obtain the average score of each cognitive evaluation indicator; processing the average score of each cognitive evaluation indicator using a weighted average method to obtain the user's cognitive health level; and obtaining the user's cognitive health assessment result based on the cognitive health level, the average score of each cognitive evaluation indicator, and a preset cognitive health assessment library.

[0012] Preferably, the processing procedure of the preset scenario analysis model includes: processing the recorded dataset using the analytic hierarchy process (AHP); specifically including: a data processing layer, which divides the recorded dataset according to a set time interval and averages the recorded dataset within the set time interval to obtain a first dataset arranged in chronological order; a factor data acquisition layer, which inputs the data in the first dataset into the corresponding influencing factor dataset according to the influencing factors corresponding to each cognitive evaluation indicator; and a scoring determination layer, which merges the respective influencing factor datasets according to the preset analysis rules of each cognitive evaluation indicator to obtain the average score of each cognitive evaluation indicator.

[0013] Preferably, the decision generation module analyzes abnormal data in the cognitive health assessment results to determine the cause of the abnormality, specifically including: obtaining a first set of records in which the average score of each cognitive evaluation indicator is lower than the corresponding preset standard score; obtaining an abnormal set of records in the first set of records that is lower than the corresponding preset standard value; determining the abnormal influencing factors based on the degree of deviation between the abnormal set of records and the corresponding preset standard value, and determining the abnormality level based on the degree of deviation between the degree of deviation and the preset standard; and obtaining the cause of the abnormality based on the abnormal set of records, the abnormal influencing factors, and the abnormality level.

[0014] Preferably, determining the abnormal influencing factors based on the degree of deviation between the abnormal dataset and the corresponding preset standard value includes: the calculation formula for the degree of deviation d between the abnormal data and the corresponding preset standard value is:

[0015]

[0016] Where n is the number of identical anomalous data items sorted chronologically, and a i For the i-th anomalous data in the same type of anomalous data, a i1 For a i The corresponding preset upper limit or preset lower limit, a i0 For a i The corresponding preset standard value; when the deviation degree is greater than the corresponding preset deviation degree value, the abnormal dataset corresponding to the deviation degree is the abnormal impact dataset. Based on the correspondence between each abnormal impact dataset and the association information database of abnormal impact factors, the abnormal impact factors are determined.

[0017] Preferably, the cognitive health management module includes: selecting corresponding rehabilitation training scenarios from a preset rehabilitation scenario training library based on the required scenarios in the scenario training decision; generating an initial rehabilitation training plan based on the correspondence between the scenario training decision, the rehabilitation training scenarios, and the preset rehabilitation training plan; and adjusting the initial rehabilitation training plan based on user feedback information to obtain a rehabilitation training plan that meets the user's needs.

[0018] Preferably, the data acquisition module includes: using an audio acquisition device installed on the VR headset to collect the user's audio data in real time; and synchronizing the audio data in real time to the VR video of the recorded interactive scene to form audio and video data; and using a VR headset, VR controller and multiple detection devices to collect various body data of the user in real time.

[0019] Preferably, an elderly cognitive health management system based on virtual reality technology further includes: a scene generation module, used to generate corresponding scenes based on newly added scene database data; specifically including: classifying the newly added scene database data according to a preset type to obtain new scene data; and adjusting a preset scene template of a preset type constructed using virtual reality technology based on the new scene data to generate the scene corresponding to the new scene data.

[0020] Preferably, the preset scene template includes at least a preset character template, a preset communication template, a preset audio template, a preset video template, and a preset environment template.

[0021] The beneficial effects of this invention are as follows:

[0022] 1. This invention employs an initial login module to acquire various user selection data and understand the user's overall information. This allows the scenario acquisition module to specifically acquire interactive scenarios that align with the user's cognitive health assessment based on the selection data, thereby improving the accuracy of the cognitive health assessment. While the user interacts within these scenarios, the data acquisition module collects various physical data and audio / video data from each interactive scenario in real time. This allows the cognitive health assessment module to analyze the physical and audio / video data to obtain the user's cognitive health assessment result. Furthermore, the decision generation module processes cognitive health assessment results with cognitive health levels below a preset level, analyzing and processing abnormal data in the cognitive health assessment results to determine the causes of the abnormalities. Based on the causes of the abnormalities and a preset information database, a cognitive health training decision is obtained. Finally, the cognitive health management module processes the scenario training decisions and user feedback information in the cognitive health training decisions to obtain rehabilitation training scenarios and plans that meet the user's needs, enabling the user to conduct cognitive rehabilitation training. This invention addresses the problem of infrequent communication between elderly individuals and doctors, leading to inaccurate diagnostic results due to insufficient data to accurately determine cognitive health levels based solely on examinations. It improves the accuracy of cognitive health assessments. Furthermore, by utilizing a decision generation module and a cognitive health management module to generate user rehabilitation training scenarios and plans, it reduces hospital visits and diagnostic time, thereby increasing diagnostic efficiency.

[0023] 2. In the cognitive health assessment module of this invention, the first step is to use an audio-visual analysis model to perform voice and image analysis on audio-visual data to obtain user performance data. Then, a preset scenario analysis model for each interaction scenario is used to fuse and evaluate the corresponding physical and performance data, obtaining the average score for each cognitive evaluation indicator. A weighted average method is then used to process the average score of each cognitive evaluation indicator to obtain the user's cognitive health level. Finally, based on the correspondence between the cognitive health level, the average score of each cognitive evaluation indicator, and the preset cognitive health assessment database, the user's cognitive health assessment result is obtained. This invention's cognitive health assessment module, in addition to analyzing various physical data, also integrates and analyzes the user's performance data in audio-visual data, making the cognitive health assessment results obtained by the module more accurate and relevant to the user's actual situation.

[0024] 3. In the cognitive health management module, this invention combines scenario training decisions and user feedback information, and can adjust the initial rehabilitation training plan according to user feedback information to obtain a rehabilitation training plan that meets the user's needs, thereby fitting the user's actual situation and improving user satisfaction. Attached Figure Description

[0025] Figure 1 This is a schematic block diagram of a cognitive health management system for the elderly based on virtual reality technology according to the present invention. Detailed Implementation

[0026] The following will refer to the attached reference. Figure 1 The various embodiments of the present invention will be described in detail below. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0027] In one embodiment of the present invention, a cognitive health management system for the elderly based on virtual reality technology is provided, as shown in the appendix. Figure 1 As shown, the system includes an initial login module, a scenario acquisition module, a data acquisition module, a cognitive health assessment module, a decision generation module, and a cognitive health management module.

[0028] The initial login module is used to obtain the selection data of the user when the user logs in for the first time.

[0029] Specifically, after the user puts on the VR device and various testing instruments, upon initial login, the user will be asked to make some choices to gain an initial understanding of their overall information. These choices include, but are not limited to, the user's education level, familiar geographical location, familiar living environment, familiar occupation, and age.

[0030] Preferably, the users described in this invention are primarily elderly people, but can also be people of other age groups.

[0031] The scene acquisition module is used to obtain the interactive scene for cognitive health assessment based on the selected data.

[0032] In the scenario acquisition module, interactive scenarios that fit users' cognition and lifestyle habits are filtered out step by step based on the selected data, so as to improve the accuracy of user cognitive health assessment.

[0033] The data acquisition module collects various physical data of users in real time, as well as audio and video data of various interactive scenarios, when users interact in various interactive scenarios.

[0034] Specifically, when users interact in various interactive scenarios, the interaction methods include, but are not limited to, controller operation, voice confirmation, and eye focus position.

[0035] The cognitive health assessment module is used to analyze various physical and audio-visual data to obtain the user's cognitive health assessment results.

[0036] Preferably, the various physical data include, but are not limited to, blood pressure, heart rate, electroencephalogram (EEG), pupil status, and blood oxygen saturation. Audio and video data include audio data collected during user interactions in various interactive scenarios and video data from interactive scenarios constructed using virtual reality technology. Cognitive health assessment results include, but are not limited to, the user's cognitive health level, the average score corresponding to each cognitive evaluation indicator, and the overall assessment result corresponding to the cognitive health level and the indicator assessment results corresponding to the average score of each cognitive evaluation indicator in a preset cognitive health assessment library.

[0037] The decision generation module analyzes abnormal data in the cognitive health assessment results when the cognitive health level is lower than the preset health level, determines the cause of the abnormality, matches the corresponding initial decision based on the cause of the abnormality and the preset information database, and generates cognitive health training decisions based on each initial decision.

[0038] Each abnormal cause corresponds to at least one initial decision. These initial decisions can be the same or different. When generating cognitive health training decisions based on these initial decisions, the initial decisions with the highest repetition frequency are prioritized as the content of the cognitive training decisions. Once the content added to the cognitive health training decisions covers all abnormal causes, no new content is added, and the final cognitive health training decisions are formed directly.

[0039] Preferably, the preset health level is typically 60, but can be adjusted according to actual conditions. Initial decisions include, but are not limited to, scenario-based training decisions, dietary decisions, and exercise decisions. Cognitive health training decisions include, but are not limited to, scenario-based training decisions, dietary decisions, and exercise decisions. The preset information database is a database established by experts in cognitive health management, detailing the correspondence between various abnormal causes and each initial decision.

[0040] The cognitive health management module is used to obtain scenario training decisions in cognitive health training decision-making. Based on scenario training decisions and user feedback information, it matches the corresponding rehabilitation training scenarios and rehabilitation training plans, and regularly uses the cognitive health assessment module to evaluate the results of rehabilitation training in order to adjust the rehabilitation training plan based on the assessment results.

[0041] The cognitive health management module combines scenario-based training decisions and user feedback information. It can adjust the initial rehabilitation training plan based on user feedback to obtain a rehabilitation training plan that meets the user's needs, thereby aligning with the user's actual situation and improving user satisfaction.

[0042] In this embodiment, the invention employs an initial login module to acquire various selection data from the user, gaining an understanding of the user's overall information. This allows the scene acquisition module to specifically acquire interactive scenarios that align with the user's cognitive health assessment based on the selection data, thereby improving the accuracy of the cognitive health assessment. While the user interacts within these scenarios, the data acquisition module collects various physical data from the user in real time, along with audio and video data from each interactive scenario. This allows the cognitive health assessment module to analyze the physical and audio / video data to obtain the user's cognitive health assessment result. Furthermore, the decision generation module processes cognitive health assessment results with cognitive health levels below a preset level, analyzing and processing abnormal data in the cognitive health assessment results to determine the causes of the abnormalities. Based on the causes of the abnormalities and a preset information database, a cognitive health training decision is generated. Finally, the cognitive health management module processes the scenario training decisions and user feedback information in the cognitive health training decisions to obtain rehabilitation training scenarios and plans that meet the user's needs, enabling the user to conduct cognitive rehabilitation training. This invention addresses the problem of infrequent communication between elderly individuals and doctors, leading to inaccurate diagnostic results due to insufficient data to accurately determine cognitive health levels based solely on examinations. It improves the accuracy of cognitive health assessments. Furthermore, by utilizing a decision generation module and a cognitive health management module to generate user rehabilitation training scenarios and plans, it reduces hospital visits and diagnostic time, thereby increasing diagnostic efficiency.

[0043] In one embodiment of the present invention, the scene acquisition module includes: sequentially filtering multiple scenes that match the selection data from the scene database according to the selection order of each selection data; randomly selecting a preset number of scenes from each preset type of scene using a simple random sampling method according to the preset type of scene; the preset number of scenes form various interactive scenes for cognitive health assessment in the cognitive health assessment module.

[0044] Preferably, the preset types include, but are not limited to, education level, geographical location, living environment, and job category.

[0045] Each scenario has at least one preset type. The scenario database stores virtual scenarios corresponding to various common real-world scenarios, and it is constantly being enriched and improved as more cases are added.

[0046] In this embodiment, the present invention can obtain the scenario that best matches the user's life habits through the scenario acquisition method of this embodiment, thereby helping to improve the accuracy of cognitive health assessment.

[0047] In one embodiment of the present invention, the cognitive health assessment module includes: using an audio-visual analysis model to perform voice and image analysis on audio-visual data to obtain user performance data; storing various physical data and corresponding performance data into a recording dataset of the corresponding interaction scenario in chronological order; performing fusion evaluation analysis on the corresponding recording dataset based on a preset scenario analysis model for each interaction scenario to obtain an average score for each cognitive evaluation indicator; processing the average score of each cognitive evaluation indicator using a weighted average method to obtain the user's cognitive health level; and obtaining the user's cognitive health assessment result based on the cognitive health level, the average score of each cognitive evaluation indicator, and a preset cognitive health assessment library.

[0048] Preferably, the cognitive evaluation indicators include attention indicators, orientation indicators, memory indicators, computational ability indicators, language ability indicators, visuospatial ability indicators, executive function indicators, and abstract thinking indicators. Performance data includes, but is not limited to, interaction reaction time, reaction actions, accuracy of answering questions, and number of repetitions. The construction method of the audio-visual analysis model is not limited; it can be a model built based on historical data and convolutional neural networks, or a model built based on machine learning and historical data, to achieve the analysis process of this embodiment and obtain user performance data.

[0049] In this embodiment, the cognitive health assessment module of this invention first employs an audio-visual analysis model to perform voice and image analysis on audio-visual data to obtain user performance data. Then, it uses a preset scenario analysis model for each interaction scenario to perform a fusion evaluation and analysis of the corresponding physical and performance data, obtaining the average score for each cognitive evaluation indicator. A weighted average method is then used to process the average score of each cognitive evaluation indicator to obtain the user's cognitive health level. Finally, based on the correspondence between the cognitive health level, the average score of each cognitive evaluation indicator, and a preset cognitive health assessment library, the user's cognitive health assessment result is obtained. This invention's cognitive health assessment module, in addition to analyzing various physical data, also integrates and analyzes the user's performance data in audio-visual data, making the cognitive health assessment results obtained by the module more accurate and closely aligned with the user's actual situation.

[0050] In one embodiment of the present invention, the processing procedure of the preset scenario analysis model includes: processing the recorded dataset using the analytic hierarchy process (AHP); specifically including: a data processing layer, which divides the recorded dataset according to a set time interval and averages the recorded dataset within the set time interval to obtain a first dataset arranged in chronological order; a factor data acquisition layer, which inputs the data in the first dataset into the corresponding influencing factor dataset according to the influencing factors corresponding to each cognitive evaluation indicator; and a scoring determination layer, which merges the respective influencing factor datasets according to the preset analysis rules of each cognitive evaluation indicator to obtain the average score of each cognitive evaluation indicator.

[0051] Preferably, the time interval can be set to 5s, 10s, 15s, 20s, 60s, etc., and can be set according to the actual time interval requirements of the scenario. Furthermore, the time interval varies for different time periods within the scenario and can be adjusted.

[0052] Specifically, the pre-set analysis rules for cognitive evaluation indicators include, but are not limited to: ① calculating a weighted average based on the pre-set weights of each influencing factor and the initial scores corresponding to the data of each influencing factor to obtain the average score of the cognitive evaluation indicator; ② calculating the average of the data of each influencing factor based on the correspondence between the data of each influencing factor and the initial scores to obtain the average score of the cognitive evaluation indicator. Each cognitive evaluation indicator performs fusion processing on the influencing factor dataset according to the pre-set analysis rules to determine its final average score.

[0053] In this embodiment, the preset scenario analysis model used in this invention can comprehensively and accurately obtain the average scores of each cognitive evaluation indicator based on the richness of the recorded dataset.

[0054] In one embodiment of the present invention, the decision generation module analyzes abnormal data in the cognitive health assessment results to determine the cause of the abnormality. Specifically, this includes: obtaining a first set of records in which the average score of each cognitive evaluation indicator is lower than the corresponding preset standard score; obtaining an abnormal set of records in the first set of records that is lower than the corresponding preset standard value; determining the abnormal influencing factors based on the degree of deviation between the abnormal set of records and the corresponding preset standard value, and determining the abnormality level based on the degree of deviation between the degree of deviation and the preset standard; and obtaining the cause of the abnormality based on the abnormal set of records, the abnormal influencing factors, and the abnormality level.

[0055] In this embodiment, the abnormal influencing factors are determined based on the degree of deviation between the abnormal dataset and the corresponding preset standard value, including: the formula for calculating the degree of deviation d between the abnormal data and the corresponding preset standard value is:

[0056]

[0057] Where n is the number of identical anomalous data items sorted chronologically, and a i For the i-th anomalous data in the same type of anomalous data, a i1 For a i The corresponding preset upper limit or preset lower limit, a i0 For a i The corresponding preset standard value; when the deviation degree is greater than the corresponding preset deviation degree value, the abnormal dataset corresponding to the deviation degree is the abnormal impact dataset. Based on the correspondence between each abnormal impact dataset and the association information database of abnormal impact factors, the abnormal impact factors are determined.

[0058] Preferably, the method for determining the anomaly level based on the degree of deviation and the preset standard deviation is as follows: the preset interval in which the difference between the degree of deviation and the preset standard deviation lies determines the corresponding initial anomaly level; the average value of each initial anomaly level is calculated to obtain the final anomaly level.

[0059] The method described in this embodiment of the invention can accurately identify the causes of abnormalities in the user's cognitive health assessment results, thereby facilitating the decision generation module to formulate targeted cognitive health training decisions based on the causes of abnormalities and a preset information database, so that the user can recover.

[0060] In one embodiment of the present invention, the cognitive health management module includes: selecting a corresponding rehabilitation training scenario from a preset rehabilitation scenario training library based on the required scenario in the scenario training decision; generating an initial rehabilitation training plan based on the correspondence between the scenario training decision, the rehabilitation training scenario, and the preset rehabilitation training plan; and adjusting the initial rehabilitation training plan based on user feedback information to obtain a rehabilitation training plan that meets the user's needs.

[0061] Preferably, the preset rehabilitation scenario training library includes various virtual scenarios for rehabilitation training. A corresponding relationship database is established between scenario training decisions, rehabilitation training scenarios, and preset rehabilitation training plans, enabling the matching of the corresponding preset rehabilitation training plan from this database based on the scenario training decisions and rehabilitation training scenarios. The preset rehabilitation training plan includes the training date, training duration, and current training stage for each rehabilitation training scenario.

[0062] The initial rehabilitation training plan was adjusted based on user feedback. The adjustments included the training dates, training durations, and reminder times for each rehabilitation training scenario, in order to meet the user's daily needs and not affect their daily work.

[0063] In this embodiment, the present invention combines scenario training decisions and user feedback information in the cognitive health management module, and can adjust the initial rehabilitation training plan according to the user feedback information to obtain a rehabilitation training plan that meets the user's needs, thereby conforming to the user's actual situation and improving user satisfaction.

[0064] In one embodiment of the present invention, the data acquisition module includes: using an audio acquisition device installed on the VR headset to collect the user's audio data in real time; and synchronizing the audio data in real time to the VR video of the recorded interactive scene to form audio and video data; and using a VR headset, VR controller and multiple detection devices to collect various body data of the user in real time.

[0065] In this embodiment, the present invention comprehensively acquires various physical data of the user, such as blood pressure, heart rate, brain waves, pupil status, and blood oxygen saturation, through the above-mentioned device in real time. These physical data and audio-visual data are then stored in the database corresponding to the data acquisition module in chronological order for comprehensive assessment of the cognitive health status of the elderly.

[0066] In one embodiment of the present invention, the elderly cognitive health management system based on virtual reality technology further includes a scene generation module, which is used to generate corresponding scenes based on newly added scene database data; specifically, it includes: classifying the newly added scene database data according to a preset type to obtain newly added scene data; and adjusting the preset scene template of the preset type constructed based on virtual reality technology according to the newly added scene data to generate the scene corresponding to the newly added scene data.

[0067] In this embodiment, the present invention can generate corresponding scenes based on newly added scene database data through the scene generation module, enriching the scene content in the scene database so that the selected scenes are more in line with the user's life habits, thereby helping to improve the accuracy of cognitive health assessment results.

[0068] In one embodiment of the present invention, the preset scene template includes at least a preset character template, a preset communication template, a preset audio template, a preset video template, and a preset environment template.

[0069] In this embodiment, various virtual templates are pre-built in the preset scene template, including preset character templates of various heights and work clothes, preset audio templates of various sound types, preset environment templates of various environments, and various video templates related to cognitive evaluation, so as to generate scenes.

[0070] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0071] It should be noted that in the description of this invention, terms such as "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," which indicate direction or positional relationships, are based on the direction or positional relationships shown in the accompanying drawings. These are used merely for ease of description and do not indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation; therefore, they should not be construed as limitations on this invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0072] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0073] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0074] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0075] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0076] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0077] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0078] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A cognitive health management system for the elderly based on virtual reality technology, characterized in that, The system includes: The initial login module retrieves data on the user's selected educational level, familiar geographical location, familiar living environment, and familiar work when the user logs in for the first time. The scene acquisition module obtains the interactive scenes for cognitive health assessment based on the selected data. The data acquisition module collects various physical data of users in real time when they interact in various interactive scenarios, and also collects audio and video data of various interactive scenarios. The cognitive health assessment module analyzes various physical and audio / video data to obtain the user's cognitive health assessment results. This includes: using an audio / video analysis model to perform voice and image analysis on the audio / video data to obtain the user's performance data; storing various physical data and corresponding performance data into the corresponding interactive scenario's recorded dataset in chronological order; and performing a fusion assessment analysis on the corresponding recorded datasets based on preset scenario analysis models for each interactive scenario to obtain the average score for each cognitive evaluation indicator. This includes: processing the recorded dataset using the analytic hierarchy process (AHP), including: a data processing layer that divides the recorded dataset according to a set time interval and averages the recorded datasets within that time interval to obtain a first dataset arranged in chronological order; a factor data acquisition layer that inputs the data from the first dataset into the corresponding influencing factor dataset according to the influencing factors corresponding to each cognitive evaluation indicator; and a score determination layer that fuses the respective influencing factor datasets according to preset analysis rules for each cognitive evaluation indicator to obtain the average score for each cognitive evaluation indicator. The average score of each cognitive evaluation indicator is processed using a weighted average method to obtain the user's cognitive health score; based on the cognitive health score, the average score of each cognitive evaluation indicator, and the preset cognitive health assessment library, the user's cognitive health assessment result is obtained. The decision generation module analyzes abnormal data in the cognitive health assessment results when the cognitive health score is lower than the preset health score. This analysis determines the causes of the abnormality, including: obtaining the first set of records where the average score of each cognitive evaluation indicator is lower than the corresponding preset standard score; obtaining the abnormal dataset from the first set of records that is lower than the corresponding preset standard value; and determining the influencing factors based on the degree of deviation between the abnormal dataset and the corresponding preset standard value, including the degree of deviation between the abnormal data and the corresponding preset standard value. The calculation formula is: , Where n is the number of identical anomalous data items sorted chronologically. This is the i-th anomalous data point among the same type of anomalous data. for The corresponding preset upper limit or preset lower limit, for The corresponding preset standard value; when the deviation degree is greater than the corresponding preset deviation degree value, the abnormal dataset corresponding to the deviation degree is the abnormal impact dataset. According to the correspondence between each abnormal impact dataset and the association information database of abnormal impact factors, the abnormal impact factors are determined; and the abnormal level is determined according to the deviation degree and the preset standard deviation degree; the abnormal cause is obtained according to the abnormal dataset, abnormal impact factors and abnormal level; the corresponding initial decision is matched according to the abnormal cause and the preset information database; and cognitive health training decisions are generated according to each initial decision. The cognitive health management module is used to obtain scenario training decisions in cognitive health training decision-making. Based on scenario training decisions and user feedback information, it matches the corresponding rehabilitation training scenarios and rehabilitation training plans, and regularly uses the cognitive health assessment module to evaluate the results of rehabilitation training in order to adjust the rehabilitation training plan based on the assessment results.

2. The cognitive health management system according to claim 1, characterized in that, The scenario acquisition module includes: sequentially filtering multiple scenarios that match the selected data from the scenario database according to the selection order of each selected data; randomly selecting a preset number of scenarios from each scenario of the preset type using a simple random sampling method according to the preset type of the scenarios; the preset number of scenarios form the various interactive scenarios used for cognitive health assessment in the cognitive health assessment module.

3. The cognitive health management system according to claim 1, characterized in that, The cognitive health management module includes: selecting corresponding rehabilitation training scenarios from a preset rehabilitation scenario training library based on the required scenarios in the scenario training decision; generating an initial rehabilitation training plan based on the correspondence between the scenario training decision, the rehabilitation training scenario, and the preset rehabilitation training plan; and adjusting the initial rehabilitation training plan based on user feedback information to obtain a rehabilitation training plan that meets the user's needs.

4. The cognitive health management system according to claim 1, characterized in that, The data acquisition module includes: using an audio acquisition device installed on the VR headset to collect the user's audio data in real time; and synchronizing the audio data in real time to the VR video of the recorded interactive scene to form audio and video data; and using a VR headset, VR controller and multiple detection devices to collect various body data of the user in real time.

5. The cognitive health management system according to claim 1 or 2, characterized in that, Also includes: The scene generation module is used to generate corresponding scenes based on newly added scene database data. Specifically, it includes: classifying the newly added scene database data according to preset types to obtain new scene data; adjusting the preset scene templates of preset types constructed based on virtual reality technology according to the new scene data to generate the scene corresponding to the new scene data; the preset scene templates include at least preset character templates, preset communication templates, preset audio templates, preset video templates, and preset environment templates.

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